Rishi Jha
Student Researcher at Google
United States
Summary
👤
Senior🎓
Top SchoolRishi Jha is a PhD student researcher at Cornell Tech with nine years of industry and research experience at the intersection of machine learning, security, and agentic systems. He studies how generative models encode knowledge and leverages that insight to design safer multi-agent and alignment defenses, with recent work on the universal geometry of embeddings and agentic security. Rishi has shipped and productionized defenses at Microsoft (including a patent-pending spectral detection approach and a proposed core safety layer for multi-agent deployments) and is currently investigating agentic security at Google. His research background spans high-impact backdoor and robustness work—e.g., FLIP, a trajectory-matching label-poisoning attack that achieves near-perfect success with minimal data poisoning—alongside applied systems engineering from startups to enterprise products. Collected training in CS and math (UW MS and BS, now Cornell PhD) complements his ability to move ideas from theory to deployed safeguards. An uncommon throughline in his work is pairing principled theoretical insight about representations with pragmatic, testable defenses that teams adopt.
9 years of coding experience
4 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of WashingtonThe Overlake SchoolDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Cornell University
Stackoverflow
1reputation
0reached
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Github Skills (4)
lte8
testing6
machine-learning6
jekyll3
Programming languages (5)
Github contributions (5)
rjha18/new_site
Apr 2019 - Sep 2025
Contributions:111 pushes, 1 branch in 6 years 6 months
SewoongLab/backdoor-suite
May 2021 - Jan 2023
A module-based repository for testing and evaluating backdoor attacks and defenses.
Contributions:38 commits, 2 PRs, 13 pushes in 1 year 8 months
testingbackdoor-attacksmachine-learning
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